How Congress Is Approaching AI’s Labor Market Impacts
A Summary and Assessment of Recently Introduced Bills
The effect of AI on the American workforce is of bipartisan concern in Congress and is likely to feature prominently in future policy debates. This policy brief describes recent legislative proposals addressing AI’s impacts on the workforce, examines open questions about their effectiveness, and identifies gaps that future legislation may need to fill.
Between 15 March 2025 and 15 March 2026, six bills were introduced in the US House or Senate that explicitly aim to assess or address AI’s labor market impacts. These are: the AI-Related Job Impacts Clarity Act; the Workforce of the Future Act of 2025; the AI Workforce PREPARE Act; the AI Workforce Training Act; the Investing in Tomorrow’s Workforce Act of 2026; and the Economy of the Future Commission Act of 2026.
The bills have two main priorities: (1) improving data collection to measure AI’s effects on the workforce, and (2) supporting training initiatives – including pilots and program evaluations – to prepare US workers for changing workforce needs.
The effectiveness of the proposed bills remains uncertain. One key question is whether the measurement they require – like attributing layoffs to AI and identifying workers likely to be displaced – can be done reliably. Another is whether the proposed training and worker support initiatives – pilots, grants, and employer tax credits – can be scaled quickly enough if AI’s impacts arrive faster, or prove more severe, than past technological shifts.
The bills reflect policymakers’ uncertainty about how AI will reshape work and what policy responses might be needed to address these effects. This uncertainty creates a two-sided policy challenge: Overreacting to fears of AI-driven job loss could misallocate resources; underpreparing could leave workers without support to build skills and transition into new work.
These bills are first steps toward addressing AI-related labor market impacts. A more comprehensive response would likely include: further improving measurement of AI’s effects, strengthening existing worker support systems like unemployment insurance, designing labor policies that can be adjusted and scaled in line with AI’s labor impacts, and planning for scenarios in which AI drastically transforms the labor market.
